Robohub.org
 

Using 3D snapshots to control a small helicopter


by
30 September 2012



share this:

In the latest article in the Autonomous Robots journal, researchers from the Australian Defense Force Academy present a new control strategy for small flying robots that uses only vision and inertial sensors.

To control a flying robot, you usually need to know the attitude of the robot (roll, pitch, yaw), where it is in the horizontal plane (x,y), and how high it is from the ground (z). While attitude measurements are provided by inertial sensors on board the robot, most flying robots rely on GPS and additional range sensors such as ultra-sound sensors, lasers or radars to determine their position and altitude. GPS signal however is not always available in cluttered environments and can be jammed. Additional sensors increase the weight that needs to be carried by the robot. Instead Garratt et al. propose to replace position sensors with a single small, low cost camera.

By comparing a snapshot taken from a downward pointing camera and a reference snapshot taken at an earlier time, the robot is able to calculate its displacement in the horizontal plane. The loom of the image is used to calculate the change in altitude. Image loom corresponds to image expansion or contraction as can be seen in the images below. By reacting to these image displacements, the robot is able to control its position.

Grass as seen from altitudes of 0.25 m, 0.5 m, 1.0 m and 2.0 m (from left to right).

Using this strategy, the researchers were able to show in simulation that a helicopter could perform take-off, hover and the transition from low speed forward flight to hover. The ability to track horizontal and vertical displacements using 3D snapshots from a single camera was then confirmed in reality using a Vario XLC gas-turbine helicopter.

In the future, the authors intend to further test the 3D snapshot control strategy in flight using their Vario XLC helicopter before moving to smaller platforms such as an Asctec Pelican quadrotor. Additional challenges include taking into account the shadow of the robot, which might change position from snapshot to snapshot.

Source: Matthew A. Garratt, Andrew J. Lambert and Hamid Teimoori (2012) Design of a 3D snapshot based visual flight control system using a single camera in hover, Autonomous Robots.




Sabine Hauert is President of Robohub and Associate Professor at the Bristol Robotics Laboratory
Sabine Hauert is President of Robohub and Associate Professor at the Bristol Robotics Laboratory

            AUAI is supported by:



Subscribe to Robohub newsletter on substack



Related posts :

Light-activated gel could impact wearables, soft robotics, and more

  28 May 2026
In the field of ionotronics, data are transferred through ions, potentially providing a bridge between electronics and biological tissue.

Handle with care: Soft robot gripper picks ripe fruit without bruising

  27 May 2026
Stretchable fiber-optic sensors used to create a soft robot gripper.

Robot Talk Episode 157 – Generating new robot designs, with Josie Hughes

  22 May 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Josie Hughes from École Polytechnique Fédérale de Lausanne about using AI to develop new designs for robotic manipulators.

Robotics Café brings together autonomous robot practitioners

  20 May 2026
Recently launched series for researchers, students and industry practitioners aims to provide a platform for students to present their work.

Table tennis robot defeats some of world’s best players – why this has major implications for robotics

  18 May 2026
Ace, from Sony AI, is the first robot to beat elite human players in competitive physical sport.

Robot Talk Episode 156 – Rugged robots for dangerous missions, with Gavin Kenneally

  15 May 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Gavin Kenneally from Ghost Robotics about robot dogs for defence, security, and public safety.

Developing active and flexible microrobots

  13 May 2026
This class of robots opens up possibilities for biomedical applications.

How to teach the same skill to different robots

  11 May 2026
A new framework to teach a skill to robots with different mechanical designs, allowing them to carry out the same task without rewriting code for each.



AUAI is supported by:







Subscribe to Robohub newsletter on substack




 















©2026.02 - Association for the Understanding of Artificial Intelligence